Adaptation is thought to match visual coding for the environment by adjusting sensitivity so that the average responses across channels are equated. However, the characteristics of the color environment to which we are routinely adapted remain uncertain. We estimated the color statistics of the standard color environment by using a model of color coding and adaptation to predict which stimulus color distributions would be required to yield different perceptually uniform color spaces. The model was based on adapting responses in the cones and in multiple post-receptoral channels tuned to different color-luminance directions, with color and lightness based on the vector sum of the channel responses. Color spaces included the Munsell and CIE uniform spaces. For each space we calculated the relative channel sensitivities and response functions that would approximate equal perceptual steps within a given space, and then from this estimated the relative contrast and principal axes of the color distributions that would lead to these sensitivities, assuming that adaptation scales sensitivity so that all channels give the same average response to the adapting distribution. This analysis allows us to characterize the ratios of luminance and chromatic contrast that would be required to account for the perceptual balance of color for a given perceptually uniform metric and for given assumptions about adaptation and color coding, and we compare these derived distributions to actual measurements of the color statistics of scenes. For example, cone-opponent responses to uniform color metrics like the Munsell space are elongated along the blue-yellow axis, implying that channels tuned to blue-yellow variations are less sensitive because they are exposed to stronger stimulation by the environment, and this blue-yellow bias is a characteristic of many natural color environments.